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Thomas F. Golob

Researcher at University of California, Irvine

Publications -  161
Citations -  8323

Thomas F. Golob is an academic researcher from University of California, Irvine. The author has contributed to research in topics: Travel behavior & Mode choice. The author has an hindex of 48, co-authored 161 publications receiving 7958 citations. Previous affiliations of Thomas F. Golob include University of California, Santa Barbara & University of California.

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Structural equation modeling for travel behavior research

TL;DR: This review of SEM is intended to provide an introduction to the field for those who have not used the method, and a compendium of applications for Those who wish to compare experiences and avoid the pitfall of reinventing previous research.
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Demand for clean-fuel vehicles in california: a discrete-choice stated preference pilot project

TL;DR: In this paper, a study was conducted to determine how demand for clean-fuel vehicles and their fuel is likely to vary as a function of attributes that distinguish these vehicles from conventional gasoline vehicles.
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Drivers’ willingness-to-pay to reduce travel time: evidence from the San Diego I-15 congestion pricing project

TL;DR: Using revealed preference data from a congestion pricing demonstration project in San Diego, the authors estimate that willingness to pay to reduce congested travel time is higher than previous stated preference results, although this may be biased upward by drivers' perception that the toll facility provides safer driving conditions.
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A model of activity participation and travel interactions between household heads

TL;DR: In this paper, a structural model is used to explain activity interactions between heads of households and, in so doing, to explain household demand for travel, and the results suggest that a feedback mechanism should be introduced in trip generation models to reflect the effect of activity frequency and duration on the level of associated travel.

Relationships Among Urban Freeway Accidents, Traffic Flow, Weather and Lighting Conditions

TL;DR: In this article, linear and nonlinear multivariate statistical analyses are applied to determine how the types of accidents that occur on heavily used freeways in Southern California are related both to the flow of traffic and to weather and ambient lighting conditions.